The field of the disclosure relates generally to databases and more particularly to methods and apparatus for maintaining databases with a plurality of varying applicability of data for features.
In the aeronautical world, most changes that occur to navigation assets are planned and communicated well in advance of when the change actually occurs. Therefore, much of the source information processed by navigation information repositories is predictive in nature in that it describes real-world features as they are expected to exist at some specified point in the future. Navigational information repositories receive this information from a variety of sources and in a variety of formats. Generally, navigational information includes various attributes that designate the availability and applicability of the information for use in aviation products. One of those attributes includes a designator for a period of time for which the information is available (or valid) for use.
Internally, before a customer can receive navigational data products, a significant amount of work is required to analyze and process the navigational information, create assets and products from it, and deliver these products to end-users. All of this effort must be accomplished as efficiently as possible, and with careful reference to the time availability of the data, whether it is in the past, present or future. In addition, it would be useful to maintain the navigational information in such a way as to provide responses tailored to different database users (i.e., customers). Such database maintenance methods and apparatus should provide the ability to associate certain attributes with multiple effectivity dimensions in order to identify and determine the applicability of the data stored in the database for various uses. Effectivity dimensions may be either continuously valued or discrete. While the embodiments described herein are described using effectivity dimensions relevant to navigational data, other continuous effectivity dimensions include, but are not limited to ocean depth in a marine biology context, engine temperature in an automotive design context, geologic era in a paleontology context, and atmospheric pressure in an aerospace context. Further, discrete effectivity dimensions include, but are not limited to material type in an automotive design context, and cause of system failure in an aerospace context.